Searching experiment results
MLflow makes it easy to query the results of your experiments, helping you track model performance and hyperparameters.
Let's examine your most recent experiment, finding the model with the lowest Mean Absolute Percentage Error (MAPE).
本练习是课程的一部分
Designing Forecasting Pipelines for Production
练习说明
- Search MLflow runs by the
experiment_name. - Get the single best-performing model from
all_resultsbased onmetrics.mape. - Print the subset of
best_mape_model.
交互式实操练习
通过完成这段示例代码来试试这个练习。
experiment_name = "hyperparameter_tuning"
# Search MLflow runs
all_results = mlflow.____(experiment_names=[____])
# Filter for the model with the best MAPE score
best_mape_model = all_results.____("metrics.mape").head(____)
# Print the model
print(____[["params.model_name", "metrics.mape"]])